6 results about "Vector group" patented technology

The invention relates to the technical field of cable circulation monitoring, in particular to a high-voltage cable circulation monitoring method and system. The method comprises the following steps: determining a load step triggering moment and a corresponding low-load current fundamental wave vector group and a corresponding high-load current fundamental wave vector group; constructing an induced voltage deviation objective function based on the difference of the two vector groups, and iteratively determining an optimal mutual inductance coefficient vector; performing induced voltage reconstruction on the high-load current fundamental wave vector group by using the optimal mutual inductance coefficient vector, and determining a sheath loop impedance parameter based on a vector relationship between the reconstructed voltage and three-phase sheath loop current data; determining a voltage model calculation deviation degree based on the difference between the reconstruction voltage and the inversion impedance voltage drop; and the operation state of the high-voltage cable is determined. According to the method, the deviation degree and the sheath loop impedance parameter representing the conductivity of electrical connection are calculated by combining the voltage model representing the integrity of the circuit topology, and an inherent structure fault and a real resistive fault are effectively distinguished.

The method for energised conductor phase identification based on synchronous measurements using network model is performed with a system comprising a field device, a reference device and a server unit connectable to said reference and field devices, wherein the server is provided with a network model comprising information about connectivity, locations of network nodes, busbars, transformer units, field rotation, transformer vector groups and information about other phase shifting devices present in the network. In comparison to known methods, no measurements files are needed, but the identification of conductor phase is performed by matching the field device measurements to the selected reference device measurements, followed by application of the existing knowledge about network model (identification of transformers, field rotation, and connectivity in the network) and calculation of the phase shift from installed reference devices to all or selected busbars in the network model by a software installed and running either on the server, and / or the field device and / or the reference device.

The application discloses a direct torque control method and system considering DC bus voltage imbalance, and relates to the field of motor control. The method comprises the following steps: determining the distribution law of voltage vectors in the fundamental wave alpha-beta subplane and the harmonic x-y subplane when the DC bus voltage is unbalanced; determining three groups of virtual vector groups according to the distribution law and a set condition; the set condition is that the distribution of three basic voltage vectors in the harmonic x-y subplane is greater than 180 degrees, and the three basic voltage vectors are composed of two large vectors and one medium vector in the fundamental wave alpha-beta subplane; obtaining the optimal virtual vector based on the three groups of virtual vector groups according to the DC bus voltage ratio, the sector K value, the system torque and the flux demand; sorting the switches in two two-level three-phase voltage source inverters according to the action time of the three basic vectors in a control period, obtaining the optimized switch sorting, and then controlling the voltage source inverters. The application can efficiently operate under the DC bus voltage imbalance.

The invention discloses a self-calibration method, device, equipment, medium and product for an electric power meter, and relates to the field of calibration, and the method comprises the steps: obtaining a current power supply phase vector group in a set sampling period of an edge node according to the collected current power supply phase vector of each voltage channel in the electric power meter; vector difference offset processing is carried out on the current power supply phase vector set and the edge synchronization reference phase, and the comprehensive phase offset of the current period is obtained; after a power supply abnormal interruption event is detected, a zero point error estimation value is obtained according to the power supply phase vector extreme value set before power failure and the initial power supply phase vector set after power on; the zero error estimated value and the comprehensive phase offset are jointly input into the calibration correction function, the local correction factor set is updated, and a self-adaptive calibration parameter set is formed. The method is suitable for a remote deployment scene in a complex environment, and the long-term operation stability and the self-recovery capacity of the electric power meter are remarkably improved.

The application discloses a rail surface damage identification method and system based on improved discrete entropy, and equipment. The method comprises the following steps: adopting a normal cumulative distribution function to perform standardization processing on an original rail profile data sequence; generating a vector group based on the standardized sequence; corresponding each vector in the vector group with each discrete mode, and calculating the weighted probability distribution of each discrete mode according to the complexity of each vector; calculating the improved discrete entropy entropy value by adopting Rényi entropy according to the weighted probability distribution; obtaining the entropy value distribution range of each type of damage; and identifying the rail surface damage based on the improved discrete entropy entropy value and the entropy value distribution range. The application can automatically and high-precisely realize the extraction of various damage characteristics, mine valuable information in the damage data, and provide decision-making help and information support for railway staff.