Abstract: Disclosed is a power grid transmission and distribution cooperative dispatching method and system in a power market environment, relating to the technical filed of power market. The method includes: power grid transmission and distribution data are collected, and economic dispatching modeling is carried out on a hybrid system containing hydro-thermal power; linearization processing is carried out on nonlinear terms in the model; and accelerated solving is carried out on the model by adopting Benders decomposition, so that power gird transmission and distribution cooperative dispatching is optimized. The integration capacity of the power system containing hydro-thermal power to the renewable energy is enhanced, and the utilization efficiency of resources is improved, and the solving process is simplified in the present invention.

Abstract: A device for diagnosing a fault in a bearing of a motor is provided. If the device operates in a fault diagnosis mode, a current signal acquisition unit acquires a real-time current signal of the motor, a residual signal acquisition unit extracts harmonic signals from the real-time current signal of the motor acquired by the current signal acquisition unit and remove a fundamental signal and a harmonic signal from the real-time current signal of the motor to acquire a residual signal, a fault feature extraction unit analyzes the residual signal in both time domain and frequency domain to extract a fault feature index of the bearing, and a fault diagnosis model unit performs, by using a bearing fault diagnosis model obtained through training, pattern recognition on the fault feature index to diagnose a fault state of the bearing.

Abstract: A device for diagnosing a fault in a bearing of a motor is provided. If the device operates in a fault diagnosis mode, a current signal acquisition unit acquires a real-time current signal of the motor, a residual signal acquisition unit extracts harmonic signals from the real-time current signal of the motor acquired by the current signal acquisition unit and remove a fundamental signal and a harmonic signal from the real-time current signal of the motor to acquire a residual signal, a fault feature extraction unit analyzes the residual signal in both time domain and frequency domain to extract a fault feature index of the bearing, and a fault diagnosis model unit performs, by using a bearing fault diagnosis model obtained through training, pattern recognition on the fault feature index to diagnose a fault state of the bearing.