An Internet of Things (IoT) system for monitoring operation of liquefied natural gas (LNG) storage, which is realized by using a method for monitoring operation of LNG storage, wherein the IoT system includes an object platform, a sensor network platform, a management platform, a service platform, and a user platform;
- the object platform includes an LNG distributed energy storage object platform and an LNG distributed energy storage maintenance personnel object platform;
- the LNG distributed energy storage object platform is configured to monitor and perceive operating data of an LNG storage device, physical and chemical parameters of LNG and historical pressure change data in the LNG storage device, and transmit the perception information, physical and chemical parameters and the historical pressure change data after symmetric encryption to the LNG distributed energy management platform through the sensor network platform;
- and the LNG distributed energy storage maintenance personnel object platform is configured for field maintenance personnel to receive an alarm prompt and feedback on maintenance processing;
- the sensor network platform includes an LNG distributed energy storage sensor network platform and an LNG distributed energy storage maintenance personnel sensor network platform, which are configured to realize a communication connection for perception and control between the management platform and the object platform;
- the management platform is configured to acquire the operating data, the physical and chemical parameters and the historical pressure change data, determine pseudo data information based on the historical pressure change data, determining at least one set of pressure change data at at least one future time point through a pressure model based on the operating data, the physical and chemical parameters, the historical pressure change data, and the pseudo data information, wherein the pressure model is a machine learning model, the pressure model includes a feature extracting layer and a pressure layer, wherein an input of the feature extracting layer includes a forward prediction step size, the historical pressure change data, and the pseudo data information, an output of the feature extracting layer includes a pressure change feature, and the forward prediction step size is a time interval between future time points for sampling;
- an input of the pressure layer includes the pressure change feature, the operating data, and the physical and chemical parameters, and an output of the pressure layer includes the at least one set of pressure change data at the at least one future time point, and determining a pressure adjusting time point and preparing for a pressure adjustment based on the at least one set of pressure change data at the at least one future time point, send an alarm prompt to field maintenance personnel for an inspection and processing according to a tank number of the LNG storage device corresponding to the abnormal data obtained by an anomaly prediction analysis and an anomaly judgment through the sensor network platform;
- the service platform is configured to obtain perception information demanded by a user from the management platform for analysis and storage, and receive control information sent by the user for processing and send processed control information to the management platform;
- the user platform is configured to obtain the operating data of the LNG storage device from the service platform for various users and send the control information to the service platform;
- the service platform is further configured to acquire the operating data, the physical and chemical parameters, the historical pressure change data, the at least one set of pressure change data, the pressure adjusting time point demanded by a user from the management platform for analysis and storage, and receive control information sent by the user for processing and send processed control information to the management platform;
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- the user platform is further configured to obtain the operating data from the service platform, the physical and chemical parameters, the at least one set of pressure change data, the pressure adjusting time point for the user and send the control information to the service platform.