## 1 Introduction  
The temperature rise of large generator rotors in thermal power plants is one of the most important performance indicators when monitoring the status of large power equipment status. Overheating of the rotor will bring great harm to the stable operation of the generator and even the power system [1]. With an increase in generator service time, the increasingly complex power grid structure, overall forging characteristics of the rotor structure, and problems of temperature rise under unbalanced conditions have become increasingly prominent. However, at present, the methods used for the calculation of the negative-sequence temperature rise of large generators have certain drawbacks [2]. In general, the solutions to the negative-sequence problem can be divided into analytical solutions and numerical solutions [3, 4]. Analytical solutions are difficult to solve and apply to practical projects and are therefore rarely used in research. The finite-element simulation method has been widely used since the 20 th century, but it also has many limitations [5, 6]. For example, the finite-element method has the disadvantages of complex calculation, relying on mesh division and material constitutive relations, being a cumbersome and time-consuming process, and the calculation accuracy largely depending on the mesh quality [7]. Although extended finite-element analysis methods have also appeared, these methods are based on the physical level and are limited by the specific structure of the generator; therefore, the calculation result is not ideal [8, 9]. The negative-sequence working condition is essentially a dynamic changing process. The whole process changes rapidly and the trend is unpredictable in some cases. In this process, massive system data, equipment data, main parameter change data, and load data are generated [10; 11; 12; 13]. It is obvious that these data are highly time-sensitive and volatile, and require a powerful, high-speed and accurate calculation method for information processing to carry out relevant analysis and calculation of state prediction, equipment evaluation and system optimization operation, and to realize a series of professional operations with strong effectiveness, such as dynamic decision-making and accident handling [14; 15; 16]. Therefore, the speed and trend of generator performance change can be obtained to a certain extent, and the approximate trend of negative-sequence temperature rise can be determined through in-depth mining, intelligent calculation of real-time monitoring of characteristic data, and timely prediction of the change trends of rotor temperature rise [17; 18]. This is of great significance for monitoring the real-time operation performance and power generation efficiency of large generators, saving maintenance costs and reducing the failure rate of generators. Nowadays, the increasing unit capacity of generators, as well as the corresponding increased electromagnetic load and thermal load, can easily cause local heating inside turbo-generators [19; 20; 21]. With the continuous increase in generator capacity, their volume also becomes larger and larger, and most rotors use an integral forged structure, as shown in Figure 1, which makes the harm caused by asymmetric operation more serious. At present, research on the experimental and numerical calculations of the rotor is still expanding. The dynamic balance of a rigid variable speed rotor has been tested and analyzed [22]. For an in-line arrangement of two drag-type hydrokinetic rotors, flow patterns between the two rotors and the rotor performance were investigated [23]. In [24], a novel rotor design provided better efficiency with less rotor loss but showed the disadvantage of a decreased power factor. The use of space vectors and symmetrical components of instantaneous values of currents and voltages was studied in [25].