## 2 Requirements on Computing and Data Resources of Large Generator Operation States
### Difficulties in Intelligent Computing of Operation Data  
The state prediction of a large generator mainly uses detection means and analysis and diagnosis technology to master the operation state and enhance the safety and reliability of operation. The main purpose of generator condition estimation is to find hidden dangers and faults in the operation process in time and reduce the probability of major problems. In the process of operation, the power generation quality is affected by the load of aspects such as electricity, heat, and machinery, in addition to the environment, which may lead to aging, wear, performance degradation, and other problems. At the same time, the performance of the main component materials will also decline due to the influence of high temperature, high pressure, and other factors. The occurrence of these conditions may lead to generator failure and potential safety hazards, so it is necessary to strengthen state calculation in a timely manner when an alternating magnetic field causes an eddy current loss in the solid parts that can produce or cause overheating. The operating parameters of the equipment can be obtained through sensors to reflect the running state of the equipment. However, in recent years, the running conditions of generators have become more and more complex, and the data types have become more diverse. Traditional mathematical algorithms cannot guarantee the efficiency and quality of data processing. In addition, the generator needs to monitor the surface temperature of its stator and rotor, especially the surface temperature at the position where the electromagnetic eddy current loss can easily occur at the connection of various structural parts [37; 38]. During operation, the generator carries a high line load, so even with a good ventilation system, more additional losses will be generated inside the generator under asymmetric operation, resulting in temperature rising more seriously in the main structural parts of the rotor [39]. Therefore, the surface area of the rotor is the top priority in research on temperature rise, which requires that the generator be able to bear a certain amount of unbalanced energy. The eddy current density forms on the rotor surface and the heat generated depends largely on the specific structure of the rotor itself. If the rotor body produces a large temperature-rise gradient, then any uneven expansion, elongation, or deformation will inevitably cause damage to the generator rotor, and in serious cases, cracks may appear, greatly reducing its fatigue life [40; 41]. The state data of the generator include the current and voltage recording data of three-phase lines and neutral lines, infrared data, ultraviolet data, and visible light tilt photography data (which provide a reference for infrared and ultraviolet data) as shown in Figure 3.  
At least three voltage acquisition systems, four current acquisition systems, \(n\) visible light cameras, \(n\) infrared cameras, and \(n\) ultraviolet cameras need to be deployed. In this way, the voltage and current oscillogram information of the generator, the rotor temperature information, the creep state positioning information based on the three-dimensional real-time model, the arc and micro-arc positioning information, and the integration information of the load state are obtained. In the smart grid, circuit breaker devices are configured at the generator outlet to ensure the disconnection operation in case of system failure. Therefore, circuit breaker-related data are an essential part in the process of information collection, as shown in Figure 4.  
The redundant data extracted from the three sets can carry out 3D tilt photography and imaging of the switch, determine the positioning of the corresponding mechanism and arc positioning, and capture the temperature information of the contact and non-line parts at the same time. The levels of detail (LOD) of the switch state are transferred to the real-time 3D model.