工程实际中，如何快速准确监测感应电机转子温度对电气设备状态评估、故障预测和安全生产具有重要意义。但受运行条件限制，转子温度很难直接测得且通过间接评估方法也存在较大难度。针对这一问题，提出一种快速参数辨识的转子温度评估方法，利用转子槽谐波辨识得到转子转速，进而利用可模拟电机堵转运行的起动初始阶段的实测电参数求解得出转子电阻。将上述求解得到的转速与转子电阻，当作实时辨识转子电阻的扩展卡尔曼滤波法(EKF)所需初值，避免了初值求解迭代时间过长的问题，实现了快速在线辨识转子电阻。进而基于金属材料电阻值与温度之间的关系，求出转子实时变化温度数据。以1台22 kW感应电机为例，辨识了负载条件下的转子温度情况，验证了所提出方法的有效性与可行性。

In practice, it is very significant to monitor the rotor temperature of induction motor quickly and accurately for state evaluation, fault prediction and safety production of electrical equipment. However, due to the limitation of the real operating conditions, it is difficult to directly monitor or indirectly evaluate the rotor temperature. To solve this problem, a rapid parameter identification method for rotor temperature evaluation is proposed. The rotor speed is obtained by using the harmonic identification of rotor slot, and then the rotor resistance is obtained by measuring the electrical parameters at the initial stage of starting which can simulate the locked rotor operation of the motor. The rotor speed and resistance obtained by the above solution are regarded as the extended Kalman filter (EKF) initial value for real-time identification of rotor resistance. The proposed EKF method avoids the problem of long iterative time of initial value, and realizes the rapid on-line identification of rotor resistance. Based on the relationship between the resistance value of metal material and the temperature, the real-time temperature data of rotor can be obtained. Taking a 22 kW induction motor as an example, the rotor temperature under different load conditions is identified, and the validity and feasibility of the proposed method are verified.