Patent ID: 11921169
Assignee: WUHAN UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 14:
15. A transformer fault diagnosis system using induced ordered weighted evidence reasoning, comprising a processor, wherein the processor is configured to:
load typical data samples of a transformer FRA and set a diagnostic label as an identification framework; wherein the typical data sample of the transformer FRA is detected by voltage detectors, which are connected to end terminals of a transformer;
load test data of a device to be diagnosed;
calculate basic probability assignments of a detection data curve of the device to be diagnosed and all characteristic data curves in the identification framework, and construct a reliability decision matrix;
calculate an induced ordered weighted averaging operator and its induction vector according to a sample source of the test data of the device to be diagnosed;
calculate an index weight vector; and
fuse all evidence by the induced ordered weighted evidence theory and calculate reliability of comprehensive evaluation, so as to determine a diagnosis result;
wherein the processor is further configured to:
divide a detection data curve X0 of the device to be diagnosed and a characteristic data curve Xl in the identification framework into NSEC segments in a same manner, with X0=[X01, X02, . . . , X0k, . . . , X0NSEC], X=[Xl1, Xl2, . . . , Xlk, . . . , XINSEC], where X0k represents a k-th segment after division of X0, Xlk represents a k-th segment after division of an l-th curve Xl in the identification framework, where k=1, 2, . . . NSEC; wherein the identification framework comprises a plurality of fault types and uncertainty result, and the fault types comprises winding short circuit, longitudinal deformation, and axial deformation; and
calculate a distance Pk, l between each segment of the detection data curve of the device to be diagnosed and all the characteristic data curves in the identification framework through a curve similarity algorithm, and convert the distance of each curve into a reliability βk, l.